While the use of automated production and assembly systems in product manufacturing is well known, such work is still predominately accomplished manually by human operators. In a typical manufacturing facility, one or more operators may be required to build one or more assemblies using a number of tools, steps and component parts. Such operations are subject to a number of opportunities for error i.e. omission of required parts, use of the wrong assembly tool, use of the wrong part in a particular location, incorrect torque, etc. These problems are only compounded in facilities where numerous models or variations of parts are assembled on the same line. Such errors or defects, if left undiscovered result in recalls, rejections by customers or returns or warranty claims by end users, all causing a great deal of expense for the manufacturer, distributor and dealer, and a general dissatisfaction among end users. The flowchart of FIG. 1 illustrates a typical assembly process as may be used in a product manufacturing facility. At 101 a product enters a workstation. At 102 the operator identifies the particular product model from a paper schedule. At 103 the operator identifies the work to be performed for the particular product model from a paper subschedule document. The operator then performs the required work from the subschedule document at 104. When the operator determines that all required work has been completed, the operator at 105 moves the product to the next workstation. At this point 106 no means are in place to confirm whether all required work has been performed. Thus the product is moved down the line with all required work having been completed or without all required work having been completed, resulting in a good product at 108 in the first instance or a defective product at 107 in the second instance. In either instance the product is passed down the line and the operator starts the process over on the next product at 109. Accordingly, an unacceptable percentage of products are passed down the line without all assembly steps having been completed. In some cases the defect is discovered at subsequent workstations and is later remedied, but in some cases the product makes it all the way to the end user before the defect is discovered.
Thus, in recent years a concerted effort has been made by many manufacturers to improve quality and reduce manufacturing errors or defects. The effort to improve the quality of products and attain cost savings by the manufacture of products without error is a continuous goal. A number of efforts to attain these goals have been attempted in the past. However, in the assembly process the human factor is difficult to include in a mistake-proofing system. Numerous tools and techniques have been developed to aid in controlling the assembly process, but attempts to date have only been capable of monitoring single product configurations or are so expensive and complicated to configure, deploy and sustain that they are virtually impractical. Some of these efforts do well to transfer design knowledge and make it accessible to manufacturing operators, yet stop short of the actual control of the manufacturing process. Other initiatives combine instructional information and testing with process reporting. These are limited to not allowing the display of the next instruction set and instructions are specific to each product. This strategy is good, but in a manufacturing situation where an assembly line has significant variability in product configuration, it is not manageable. Other known efforts incorporate a variety of sensing devices into the monitoring of a machining process. In this approach, the machine is pre-programmed and the variability of human actions do not come into play, and the resultant corrections of machine function to correct a sensed error must be programmed as well. Still other approaches go to considerable effort to assure that the correct part combinations in a significantly variable assembly process are available and managed. While these approaches do much toward always knowing where a product is in the assembly process and that the components are available and accounted for, they do not go beyond this component matching, and tracking strategy to improve quality. In order to be practical, mistake-proofing must be order specific at the component level and must be adaptable to mixed model production scenarios. First and foremost the human factor must be assured.
As such, there is a clear need in the art for a holistic, order specific mistake-proofing system for assembly operations which is infinitely variable and adaptable to a variety of manufacturing scenarios, while addressing the human factor. Without the mistake-proofing method described below, the number of methods, tools, and options for mistake-proofing are limited by a variety of typical assembly process complications that limit what methods can be used to solve individual process or part verification techniques. Such things as product option configurations, mixed model production, and cycle time at a given assembly station make previous solutions impractical.